A PINN approach learns nearly maximal Lyapunov functions via Zubov's equation and verifies stability with SMT solvers.
Safe control with learned certificates: A survey of neural Lyapunov, barrier, and con- traction methods
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A literature review of safe RL using Lyapunov and barrier functions that identifies a shift to model-free methods since 2017, well-defined open problems per approach class, and high-dimensional scalability as the main barrier.
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Towards Learning and Verifying Maximal Neural Lyapunov Functions
A PINN approach learns nearly maximal Lyapunov functions via Zubov's equation and verifies stability with SMT solvers.
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A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
A literature review of safe RL using Lyapunov and barrier functions that identifies a shift to model-free methods since 2017, well-defined open problems per approach class, and high-dimensional scalability as the main barrier.